Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

Taming Regression Using APL - From Basic Linear Models to Advanced Applications

Dyalog User Meetings via YouTube

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore regression analysis techniques through APL programming in this 27-minute conference talk from Dyalog '24. Progress from basic arithmetic concepts to advanced regression methods as the speaker demonstrates how to create linear functions using Dyalog's namespaces and defined operators. Learn practical applications through real-world examples including wedding planning, car dealership advertising, and criminal investigations. Master various regression types including multiple regression, non-linear (quadratic) regression, and logistic regression for Boolean variables. Discover the TamStat statistical package, its features for data science applications, and gain insights into marketing APL applications to domain experts. Access comprehensive implementation details through downloadable presentation slides covering everything from basic regression model components to advanced statistical analysis techniques.

Syllabus

TamStat at the Symposium on Data Science and Statistics
Regression example planning a wedding
Types of regression available in TamStat
Parts of a regression model
Car dealership advertisement example with confidence and prediction intervals
Regression wizards
Multiple regression
Indicator variables murder investigation example
Non-linear quadratic regression
Logistic regression for Boolean response variable
How to download and install TamStat
Marketing your APL application to domain experts

Taught by

Dyalog User Meetings

Reviews

Start your review of Taming Regression Using APL - From Basic Linear Models to Advanced Applications

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.